Triple
T16324933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hara Sankei |
E396386
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object |
原三溪
原三溪(Hara Sankei)は、横浜の実業家であり茶人・美術収集家としても知られ、三溪園を造園したことで著名な人物である。
|
E1207567
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 原三溪 | Statement: [Hara Sankei, nativeName, 原三溪]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 原三溪 Context triple: [Hara Sankei, nativeName, 原三溪]
-
A.
溪口
溪口是位于中国浙江省奉化区的一个历史悠久的小镇,以自然风光和民俗文化闻名。
-
B.
上毛三山
上毛三山は、群馬県を代表する名峰である赤城山・榛名山・妙義山の三つの山々を総称した呼び名である。
-
C.
西堤
西堤是位于北京颐和园昆明湖西侧的一条仿杭州苏堤而建的长堤景观,以其连桥叠景和湖山胜色著称。
-
D.
三条通
三条通 is a major east–west street in central Kyoto, known for its mix of traditional shops, modern cafes, and historical atmosphere.
-
E.
Xintian (新田)
Xintian (新田) was an ancient Chinese city that served as the political and administrative center of the State of Jin during part of its history.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: 原三溪 Triple: [Hara Sankei, nativeName, 原三溪]
Generated description
原三溪(Hara Sankei)は、横浜の実業家であり茶人・美術収集家としても知られ、三溪園を造園したことで著名な人物である。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 原三溪 Target entity description: 原三溪(Hara Sankei)は、横浜の実業家であり茶人・美術収集家としても知られ、三溪園を造園したことで著名な人物である。
-
A.
溪口
溪口是位于中国浙江省奉化区的一个历史悠久的小镇,以自然风光和民俗文化闻名。
-
B.
上毛三山
上毛三山は、群馬県を代表する名峰である赤城山・榛名山・妙義山の三つの山々を総称した呼び名である。
-
C.
西堤
西堤是位于北京颐和园昆明湖西侧的一条仿杭州苏堤而建的长堤景观,以其连桥叠景和湖山胜色著称。
-
D.
三条通
三条通 is a major east–west street in central Kyoto, known for its mix of traditional shops, modern cafes, and historical atmosphere.
-
E.
Xintian (新田)
Xintian (新田) was an ancient Chinese city that served as the political and administrative center of the State of Jin during part of its history.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e296b9dcb88190beb0ca2206729175 |
completed | April 17, 2026, 8:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00260ca9f08190aa95560fea482dd4 |
completed | May 10, 2026, 6:30 a.m. |
| NEDg | Description generation | batch_6a0027a095508190b7c6fd56af289e7b |
completed | May 10, 2026, 6:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00282d9b0c81908031404c41b3baa5 |
completed | May 10, 2026, 6:39 a.m. |
Created at: April 10, 2026, 5:06 a.m.